From d740acce513b78c45d92b388eb003e01f43c7388 Mon Sep 17 00:00:00 2001
From: wjj19950828 <wjjisloser@163.com>
Date: Sun, 9 Oct 2022 19:33:03 +0800
Subject: [PATCH] fixed ToPILImage

---
 .../torchvision.transforms.ToPILImage.md      | 33 ++++++++++---------
 1 file changed, 17 insertions(+), 16 deletions(-)

diff --git a/docs/pytorch_project_convertor/API_docs/vision/torchvision.transforms.ToPILImage.md b/docs/pytorch_project_convertor/API_docs/vision/torchvision.transforms.ToPILImage.md
index 7c1c684..f377590 100644
--- a/docs/pytorch_project_convertor/API_docs/vision/torchvision.transforms.ToPILImage.md
+++ b/docs/pytorch_project_convertor/API_docs/vision/torchvision.transforms.ToPILImage.md
@@ -18,7 +18,8 @@ from paddle.vision.transforms import functional as F
 
 class ToPILImage(BaseTransform):
     def __init__(self, mode=None, keys=None):
-        super(ToTensor, self).__init__(keys)
+        super(ToPILImage, self).__init__(keys)
+        self.mode = mode
 
     def _apply_image(self, pic):
         """
@@ -53,7 +54,7 @@ class ToPILImage(BaseTransform):
 
         npimg = pic
         if isinstance(pic, paddle.Tensor) and "float" in str(pic.numpy(
-        ).dtype) and mode != 'F':
+        ).dtype) and self.mode != 'F':
             pic = pic.mul(255).byte()
         if isinstance(pic, paddle.Tensor):
             npimg = np.transpose(pic.numpy(), (1, 2, 0))
@@ -74,40 +75,40 @@ class ToPILImage(BaseTransform):
                 expected_mode = 'I'
             elif npimg.dtype == np.float32:
                 expected_mode = 'F'
-            if mode is not None and mode != expected_mode:
+            if self.mode is not None and self.mode != expected_mode:
                 raise ValueError(
                     "Incorrect mode ({}) supplied for input type {}. Should be {}"
-                    .format(mode, np.dtype, expected_mode))
-            mode = expected_mode
+                    .format(self.mode, np.dtype, expected_mode))
+            self.mode = expected_mode
 
         elif npimg.shape[2] == 2:
             permitted_2_channel_modes = ['LA']
-            if mode is not None and mode not in permitted_2_channel_modes:
+            if self.mode is not None and self.mode not in permitted_2_channel_modes:
                 raise ValueError("Only modes {} are supported for 2D inputs".
                                  format(permitted_2_channel_modes))
 
-            if mode is None and npimg.dtype == np.uint8:
-                mode = 'LA'
+            if self.mode is None and npimg.dtype == np.uint8:
+                self.mode = 'LA'
 
         elif npimg.shape[2] == 4:
             permitted_4_channel_modes = ['RGBA', 'CMYK', 'RGBX']
-            if mode is not None and mode not in permitted_4_channel_modes:
+            if self.mode is not None and self.mode not in permitted_4_channel_modes:
                 raise ValueError("Only modes {} are supported for 4D inputs".
                                  format(permitted_4_channel_modes))
 
-            if mode is None and npimg.dtype == np.uint8:
-                mode = 'RGBA'
+            if self.mode is None and npimg.dtype == np.uint8:
+                self.mode = 'RGBA'
         else:
             permitted_3_channel_modes = ['RGB', 'YCbCr', 'HSV']
-            if mode is not None and mode not in permitted_3_channel_modes:
+            if self.mode is not None and self.mode not in permitted_3_channel_modes:
                 raise ValueError("Only modes {} are supported for 3D inputs".
                                  format(permitted_3_channel_modes))
-            if mode is None and npimg.dtype == np.uint8:
-                mode = 'RGB'
+            if self.mode is None and npimg.dtype == np.uint8:
+                self.mode = 'RGB'
 
-        if mode is None:
+        if self.mode is None:
             raise TypeError('Input type {} is not supported'.format(
                 npimg.dtype))
 
-        return Image.fromarray(npimg, mode=mode)
+        return Image.fromarray(npimg, mode=self.mode)
 ```
-- 
GitLab